OpenRaiser/Intern-Atlas huggingface dataset:
Intelligent Systems: Architectures and Perspectives
Venue: arXiv cs.AI 2004
Year: 2004

The integration of different learning and adaptation techniques to overcome individual limitations and to achieve synergetic effects through the hybridization or fusion of these techniques has, in recent years, contributed to a large number of new intelligent system designs. Computational intelligence is an innovative framework for constructing intelligent hybrid architectures involving Neural Networks (NN), Fuzzy Inference Systems (FIS), Probabilistic Reasoning (PR) and derivative free optimization techniques such as Evolutionary Computation (EC). Most of these hybridization approaches, however, follow an ad hoc design methodology, justified by success in certain application domains. Due to the lack of a common framework it often remains difficult to compare the various hybrid systems conceptually and to evaluate their performance comparatively. This chapter introduces the different generic architectures for integrating intelligent systems. The designing aspects and perspectives of different hybrid archirectures like NN-FIS, EC-FIS, EC-NN, FIS-PR and NN-FIS-EC systems are presented. Some conclusions are also provided towards the end.
Meta-Learning Evolutionary Artificial Neural Networks
Venue: arXiv cs.AI 2004
Year: 2004

In this paper, we present MLEANN (Meta-Learning Evolutionary Artificial Neural Network), an automatic computational framework for the adaptive optimization of artificial neural networks wherein the neural network architecture, activation function, connection weights; learning algorithm and its parameters are adapted according to the problem. We explored the performance of MLEANN and conventionally designed artificial neural networks for function approximation problems. To evaluate the comparative performance, we used three different well-known chaotic time series. We also present the state of the art popular neural network learning algorithms and some experimentation results related to convergence speed and generalization performance. We explored the performance of backpropagation algorithm; conjugate gradient algorithm, quasi-Newton algorithm and Levenberg-Marquardt algorithm for the three chaotic time series. Performances of the different learning algorithms were evaluated when the activation functions and architecture were changed. We further present the theoretical background, algorithm, design strategy and further demonstrate how effective and inevitable is the proposed MLEANN framework to design a neural network, which is smaller, faster and with a better generalization performance.
A Probabilistic Model of Machine Translation
Venue: arXiv cs.CL 2004
Year: 2004

A probabilistic model for computer-based generation of a machine translation system on the basis of English-Russian parallel text corpora is suggested. The model is trained using parallel text corpora with pre-aligned source and target sentences. The training of the model results in a bilingual dictionary of words and "word blocks" with relevant translation probability.
Culture and International Usability Testing: The Effects of Culture in Structured Interviews
Venue: arXiv cs.HC 2004
Year: 2004

The global audience for software products includes members of different countries, religions, and cultures: people who speak different languages, have different life styles, and have different perceptions and expectations of any given product. A major impediment in interface development is that there is inadequate empirical evidence for the effects of culture in the usability engineering methods used for developing user interfaces. This paper presents a controlled study investigating the effects of culture on the effectiveness of structured interviews in usability testing. The experiment consisted of usability testing of a website with two independent groups of Indian participants by two interviewers; one belonging to the Indian culture and the other to the Anglo-American culture. Participants found more usability problems and made more suggestions to an interviewer who was a member of the same (Indian) culture than to the foreign (Anglo-American) interviewer. The results of the study empirically establish that culture significantly affects the efficacy of structured interviews during international user testing. The implications of this work for usability engineering are discussed.
Soft Computing Models for Network Intrusion Detection Systems
Venue: arXiv cs.CR 2004
Year: 2004

Security of computers and the networks that connect them is increasingly becoming of great significance. Computer security is defined as the protection of computing systems against threats to confidentiality, integrity, and availability. There are two types of intruders: external intruders, who are unauthorized users of the machines they attack, and internal intruders, who have permission to access the system with some restrictions. This chapter presents a soft computing approach to detect intrusions in a network. Among the several soft computing paradigms, we investigated fuzzy rule-based classifiers, decision trees, support vector machines, linear genetic programming and an ensemble method to model fast and efficient intrusion detection systems. Empirical results clearly show that soft computing approach could play a major role for intrusion detection.
The model of the tables in design documentation for operating with the electronic catalogs and for specifications making in a CAD system
Venue: arXiv cs.CE 2004
Year: 2004

The hierarchic block model of the tables in design documentation as a part of a CAD system is described, intended for automatic specifications making of elements of the drawings, with usage of the electronic catalogs. The model is created for needs of a CAD system of reconstruction of the industrial plants, where the result of designing are the drawings, which include the specifications of different types. The adequate simulation of the specification tables is ensured with technology of storing in the drawing of the visible geometric elements and invisible parametric representation, sufficient for generation of this elements.
Modular technology of developing of the extensions of a CAD system. Axonometric piping diagrams. Parametric representation
Venue: arXiv cs.CE 2004
Year: 2004

Applying the modular technology of developing of the problem-oriented extensions of a CAD system to a problem of automation of creating of the axonometric piping diagrams on an example of the program system TechnoCAD GlassX is described. The proximity of composition of the schemas is detected for special technological pipe lines, systems of a water line and water drain, heating, heat supply, ventilating, air conditioning. The structured parametric representation of the schemas, including properties of objects, their link, common settings, settings by default and the special links of compatibility is reviewed.
Jigsaw-based Security in Data Transfer in Computer Networks
Venue: arXiv cs.CR 2004
Year: 2004

In this paper, we present a novel encryption-less algorithm to enhance security in transmission of data in networks. The algorithm uses an intuitively simple idea of a 'jigsaw puzzle' to break the transformed data into multiple parts where these parts form the pieces of the puzzle. Then these parts are packaged into packets and sent to the receiver. A secure and efficient mechanism is provided to convey the information that is necessary for obtaining the original data at the receiver-end from its parts in the packets, that is, for solving the 'jigsaw puzzle'. The algorithm is designed to provide information-theoretic (that is, unconditional) security by the use of a one-time pad like scheme so that no intermediate or unintended node can obtain the entire data. An authentication code is also used to ensure authenticity of every packet.
Grid Databases for Shared Image Analysis in the MammoGrid Project
Venue: arXiv cs.DB 2004
Year: 2004

The MammoGrid project aims to prove that Grid infrastructures can be used for collaborative clinical analysis of database-resident but geographically distributed medical images. This requires: a) the provision of a clinician-facing front-end workstation and b) the ability to service real-world clinician queries across a distributed and federated database. The MammoGrid project will prove the viability of the Grid by harnessing its power to enable radiologists from geographically dispersed hospitals to share standardized mammograms, to compare diagnoses (with and without computer aided detection of tumours) and to perform sophisticated epidemiological studies across national boundaries. This paper outlines the approach taken in MammoGrid to seamlessly connect radiologist workstations across a Grid using an "information infrastructure" and a DICOM-compliant object model residing in multiple distributed data stores in Italy and the UK
An Abductive Framework For Computing Knowledge Base Updates
Venue: arXiv cs.DB 2004
Year: 2004

This paper introduces an abductive framework for updating knowledge bases represented by extended disjunctive programs. We first provide a simple transformation from abductive programs to update programs which are logic programs specifying changes on abductive hypotheses. Then, extended abduction, which was introduced by the same authors as a generalization of traditional abduction, is computed by the answer sets of update programs. Next, different types of updates, view updates and theory updates are characterized by abductive programs and computed by update programs. The task of consistency restoration is also realized as special cases of these updates. Each update problem is comparatively assessed from the computational complexity viewpoint. The result of this paper provides a uniform framework for different types of knowledge base updates, and each update is computed using existing procedures of logic programming.
An Analysis of Lambek's Production Machines
Venue: arXiv cs.LO 2004
Year: 2004

Lambek's production machines may be used to generate and recognize sentences in a subset of the language described by a production grammar. We determine in this paper the subset of the language of a grammar generated and recognized by such machines.
CLAIRE: Combining Sets, Search And Rules To Better Express Algorithms
Venue: arXiv cs.PL 2004
Year: 2004

This paper presents a programming language which includes paradigms that are usually associated with declarative languages, such as sets, rules and search, into an imperative (functional) language. Although these paradigms are separately well known and are available under various programming environments, the originality of the CLAIRE language comes from the tight integration, which yields interesting run-time performances, and from the richness of this combination, which yields new ways in which to express complex algorithmic patterns with few elegant lines. To achieve the opposite goals of a high abstraction level (conciseness and readability) and run-time performance (CLAIRE is used as a C++ preprocessor), we have developed two kinds of compiler: first, a pattern pre-processor handles iterations over both concrete and abstract sets (data types and program fragments), in a completely user-extensible manner; secondly, an inference compiler transforms a set of logical rules into a set of functions (demons that are used through procedural attachment).
Blind Detection and Compensation of Camera Lens Geometric Distortions
Venue: arXiv cs.CV 2004
Year: 2004

This paper presents a blind detection and compensation technique for camera lens geometric distortions. The lens distortion introduces higher-order correlations in the frequency domain and in turn it can be detected using higher-order spectral analysis tools without assuming any specific calibration target. The existing blind lens distortion removal method only considered a single-coefficient radial distortion model. In this paper, two coefficients are considered to model approximately the geometric distortion. All the models considered have analytical closed-form inverse formulae.
Knowledge Reduction and Discovery based on Demarcation Information
Venue: arXiv cs.LG 2004
Year: 2004

Knowledge reduction, includes attribute reduction and value reduction, is an important topic in rough set literature. It is also closely relevant to other fields, such as machine learning and data mining. In this paper, an algorithm called TWI-SQUEEZE is proposed. It can find a reduct, or an irreducible attribute subset after two scans. Its soundness and computational complexity are given, which show that it is the fastest algorithm at present. A measure of variety is brought forward, of which algorithm TWI-SQUEEZE can be regarded as an application. The author also argues the rightness of this measure as a measure of information, which can make it a unified measure for "differentiation, a concept appeared in cognitive psychology literature. Value reduction is another important aspect of knowledge reduction. It is interesting that using the same algorithm we can execute a complete value reduction efficiently. The complete knowledge reduction, which results in an irreducible table, can therefore be accomplished after four scans of table. The byproducts of reduction are two classifiers of different styles. In this paper, various cases and models will be discussed to prove the efficiency and effectiveness of the algorithm. Some topics, such as how to integrate user preference to find a local optimal attribute subset will also be discussed.
Conversation Analysis and the User Experience
Venue: arXiv cs.HC 2004
Year: 2004

We provide two case studies in the application of ideas drawn from conversation analysis to the design of technologies that enhance the experience of human conversation. We first present a case study of the design of an electronic guidebook, focusing on how conversation analytic principles played a role in the design process. We then discuss how the guidebook project has inspired our continuing work in social, mobile audio spaces. In particular, we describe some as yet unrealized concepts for adaptive audio spaces.
A proposal to design expert system for the calculations in the domain of QFT
Venue: arXiv cs.AI 2004
Year: 2004

Main purposes of the paper are followings: 1) To show examples of the calculations in domain of QFT via ``derivative rules'' of an expert system; 2) To consider advantages and disadvantage that technology of the calculations; 3) To reflect about how one would develop new physical theories, what knowledge would be useful in their investigations and how this problem can be connected with designing an expert system.
Application of Business Intelligence In Banks (Pakistan)
Venue: arXiv cs.DB 2004
Year: 2004

The financial services industry is rapidly changing. Factors such as globalization, deregulation, mergers and acquisitions, competition from non-financial institutions, and technological innovation, have forced companies to re-think their business.Many large companies have been using Business Intelligence (BI) computer software for some years to help them gain competitive advantage. With the introduction of cheaper and more generalized products to the market place BI is now in the reach of smaller and medium sized companies. Business Intelligence is also known as knowledge management, management information systems (MIS), Executive information systems (EIS) and On-line analytical Processing (OLAP).
Microreboot -- A Technique for Cheap Recovery
Venue: arXiv cs.OS 2004
Year: 2004

A significant fraction of software failures in large-scale Internet systems are cured by rebooting, even when the exact failure causes are unknown. However, rebooting can be expensive, causing nontrivial service disruption or downtime even when clusters and failover are employed. In this work we separate process recovery from data recovery to enable microrebooting -- a fine-grain technique for surgically recovering faulty application components, without disturbing the rest of the application. We evaluate microrebooting in an Internet auction system running on an application server. Microreboots recover most of the same failures as full reboots, but do so an order of magnitude faster and result in an order of magnitude savings in lost work. This cheap form of recovery engenders a new approach to high availability: microreboots can be employed at the slightest hint of failure, prior to node failover in multi-node clusters, even when mistakes in failure detection are likely; failure and recovery can be masked from end users through transparent call-level retries; and systems can be rejuvenated by parts, without ever being shut down.
Image compression by rectangular wavelet transform
Venue: arXiv cs.CV 2004
Year: 2004

We study image compression by a separable wavelet basis $\big\{ψ(2^{k_1}x-i)ψ(2^{k_2}y-j),$ $ϕ(x-i)ψ(2^{k_2}y-j),$ $ψ(2^{k_1}(x-i)ϕ(y-j),$ $ϕ(x-i)ϕ(y-i)\big\},$ where $k_1, k_2 \in \mathbb{Z}_+$; $i,j\in\mathbb{Z}$; and $ϕ,ψ$ are elements of a standard biorthogonal wavelet basis in $L_2(\mathbb{R})$. Because $k_1\ne k_2$, the supports of the basis elements are rectangles, and the corresponding transform is known as the {\em rectangular wavelet transform}. We prove that if one-dimensional wavelet basis has $M$ dual vanishing moments then the rate of approximation by $N$ coefficients of rectangular wavelet transform is $\mathcal{O}(N^{-M}\log^C N)$ for functions with mixed derivative of order $M$ in each direction. The square wavelet transform yields the approximation rate is $\mathcal{O}(N^{-M/2})$ for functions with all derivatives of the total order $M$. Thus, the rectangular wavelet transform can outperform the square one if an image has a mixed derivative. We provide experimental comparison of image compression which shows that rectangular wavelet transform outperform the square one.
Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences
Venue: arXiv cs.LG 2004
Year: 2004

We present a new method for nonlinear prediction of discrete random sequences under minimal structural assumptions. We give a mathematical construction for optimal predictors of such processes, in the form of hidden Markov models. We then describe an algorithm, CSSR (Causal-State Splitting Reconstruction), which approximates the ideal predictor from data. We discuss the reliability of CSSR, its data requirements, and its performance in simulations. Finally, we compare our approach to existing methods using variable-length Markov models and cross-validated hidden Markov models, and show theoretically and experimentally that our method delivers results superior to the former and at least comparable to the latter.
Subset Queries in Relational Databases
Venue: arXiv cs.DB 2004
Year: 2004

In this paper, we motivated the need for relational database systems to support subset query processing. We defined new operators in relational algebra, and new constructs in SQL for expressing subset queries. We also illustrated the applicability of subset queries through different examples expressed using extended SQL statements and relational algebra expressions. Our aim is to show the utility of subset queries for next generation applications.
Self-organizing neural networks in classification and image recognition
Venue: arXiv cs.CV 2004
Year: 2004

Self-organizing neural networks are used for brick finding in OPERA experiment. Self-organizing neural networks and wavelet analysis used for recognition and extraction of car numbers from images.
Finite-Length Scaling for Iteratively Decoded LDPC Ensembles
Venue: arXiv cs.IT 2004
Year: 2004

In this paper we investigate the behavior of iteratively decoded low-density parity-check codes over the binary erasure channel in the so-called ``waterfall region." We show that the performance curves in this region follow a very basic scaling law. We conjecture that essentially the same scaling behavior applies in a much more general setting and we provide some empirical evidence to support this conjecture. The scaling law, together with the error floor expressions developed previously, can be used for fast finite-length optimization.
NoSEBrEaK - Attacking Honeynets
Venue: arXiv cs.CR 2004
Year: 2004

It is usually assumed that Honeynets are hard to detect and that attempts to detect or disable them can be unconditionally monitored. We scrutinize this assumption and demonstrate a method how a host in a honeynet can be completely controlled by an attacker without any substantial logging taking place.
Building a linguistic corpus from bee dance data
Venue: arXiv cs.CL 2004
Year: 2004

This paper discusses the problems and possibility of collecting bee dance data in a linguistic \textit{corpus} and use linguistic instruments such as Zipf's law and entropy statistics to decide on the question whether the dance carries information of any kind. We describe this against the historical background of attempts to analyse non-human communication systems.
Well-Definedness and Semantic Type-Checking in the Nested Relational Calculus and XQuery
Venue: arXiv cs.DB 2004
Year: 2004

Two natural decision problems regarding the XML query language XQuery are well-definedness and semantic type-checking. We study these problems in the setting of a relational fragment of XQuery. We show that well-definedness and semantic type-checking are undecidable, even in the positive-existential case. Nevertheless, for a ``pure'' variant of XQuery, in which no identification is made between an item and the singleton containing that item, the problems become decidable. We also consider the analogous problems in the setting of the nested relational calculus.
Global Grids and Software Toolkits: A Study of Four Grid Middleware Technologies
Venue: arXiv cs.DC 2004
Year: 2004

Grid is an infrastructure that involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid applications often involve large amounts of data and/or computing resources that require secure resource sharing across organizational boundaries. This makes Grid application management and deployment a complex undertaking. Grid middlewares provide users with seamless computing ability and uniform access to resources in the heterogeneous Grid environment. Several software toolkits and systems have been developed, most of which are results of academic research projects, all over the world. This chapter will focus on four of these middlewares--UNICORE, Globus, Legion and Gridbus. It also presents our implementation of a resource broker for UNICORE as this functionality was not supported in it. A comparison of these systems on the basis of the architecture, implementation model and several other features is included.
Predicate Abstraction with Indexed Predicates
Venue: arXiv cs.LO 2004
Year: 2004

Predicate abstraction provides a powerful tool for verifying properties of infinite-state systems using a combination of a decision procedure for a subset of first-order logic and symbolic methods originally developed for finite-state model checking. We consider models containing first-order state variables, where the system state includes mutable functions and predicates. Such a model can describe systems containing arbitrarily large memories, buffers, and arrays of identical processes. We describe a form of predicate abstraction that constructs a formula over a set of universally quantified variables to describe invariant properties of the first-order state variables. We provide a formal justification of the soundness of our approach and describe how it has been used to verify several hardware and software designs, including a directory-based cache coherence protocol.